Sensitivity Analysis of Ozone Formation Using Response Surface Methodology

被引:0
|
作者
Zhu, Yu-Huan [1 ]
Chen, Bing [2 ]
Zhang, Ya-Rui [1 ]
Liu, Xiao [1 ]
Li, Guang-Yao [1 ]
She, Jing [1 ]
Chen, Qiang [1 ]
机构
[1] Key Laboratory of Semi-Arid Climate Change, Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou,730000, China
[2] Focused Photonics (Hangzhou) Incorporated Company, Hangzhou,310000, China
来源
Huanjing Kexue/Environmental Science | 2023年 / 44卷 / 07期
关键词
Carbon monoxide - Nitrogen oxides - Olefins - Ozone - Sensitivity analysis - Surface properties;
D O I
10.13227/j.hjkx.202208115
中图分类号
学科分类号
摘要
Identifying the nonlinear relationship between O3 and its precursors accurately plays an important role for the policy-making of O3 pollution control. In this study, the response surface methodology based on the box model simulation was used to quickly and efficiently quantify the O3 response to their precursors with the optimal experimental design. The results showed that CO had a positive contribution to ozone generation, whereas NOx and VOCs had a significant nonlinear relationship with O3. When the ratio of φ(VOCs) to[φ(NOx)-13.75] was greater than 4.17, the ozone formation regime was NOx-limited and became VOCs-limited when the ratio was less than 4.17. Olefin was the key VOCs' component to affect the formation of O3; when the radio of φ(olefin) to[φ(NOx)-15] was less than 1.10 and the value of the φ(olefin) was less than 35×10-9, olefin went far towards generating O3. Response surface methodology demonstrated that it can be well used to explore the influence of multiple factors and their interactions on O3 formation and provides a new approach for efficient O3 sensitivity analysis. © 2023 Science Press. All rights reserved.
引用
收藏
页码:3639 / 3675
相关论文
共 50 条
  • [1] Sensitivity Analysis for Sisko Nanofluid Flow Through Stretching Surface Using Response Surface Methodology
    Upreti, Himanshu
    Uddin, Ziya
    Pandey, Alok Kumar
    Joshi, Navneet
    [J]. NANO, 2024,
  • [2] Sensitivity Analysis of Flux Cored Arc Cladding Parameters Using Response Surface Methodology
    Kannan, T.
    Murugan, N.
    [J]. JOURNAL FOR MANUFACTURING SCIENCE AND PRODUCTION, 2006, 7 (3-4) : 171 - 185
  • [3] Response Surface Methodology Applied to Ozone Generation
    Mochi, Vanessa Trevizan
    Pacheco, Jose Ricardo
    Cremasco, Marco Aurelio
    [J]. OZONE-SCIENCE & ENGINEERING, 2010, 32 (05) : 372 - 378
  • [4] Sensitivity analysis of process parameters in PTA hardfacing of valve seats using response surface methodology
    Marimuthu, K
    Murugan, N
    [J]. MATERIALS SCIENCE AND TECHNOLOGY, 2005, 21 (08) : 941 - 947
  • [5] Sensitivity analysis of process parameters for granular mixing in an intensive mixer using response surface methodology
    Zuo, Zhijian
    Gong, Shuguang
    Xie, Guilan
    Zhang, Jianping
    [J]. POWDER TECHNOLOGY, 2021, 384 : 51 - 61
  • [6] Thermal optimization of MHD nanofluid over a wedge by using response surface methodology: Sensitivity analysis
    Zeeshan, Ahmed
    Hussain, Dilawar
    Asghar, Zaheer
    Bhatti, Muhammad Mubashir
    Duraihem, Faisal Z.
    [J]. PROPULSION AND POWER RESEARCH, 2023, 12 (04) : 556 - 567
  • [7] Source contributions of surface ozone in China using an adjoint sensitivity analysis
    Wang, M. Y.
    Yim, Steve H. L.
    Wong, D. C.
    Ho, K. F.
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 662 : 385 - 392
  • [8] Optimization of Reactive Blue 19 dye removal using ozone and ozone/UV employing response surface methodology
    Mariana Guadalupe Abrile
    María Laura Fiasconaro
    María Eugenia Lovato
    [J]. SN Applied Sciences, 2020, 2
  • [9] Optimization of Reactive Blue 19 dye removal using ozone and ozone/UV employing response surface methodology
    Guadalupe Abrile, Mariana
    Laura Fiasconaro, Maria
    Eugenia Lovato, Maria
    [J]. SN APPLIED SCIENCES, 2020, 2 (05):
  • [10] Sensitivity analysis of particle contact parameters for DEM simulation in a rotating drum using response surface methodology
    Rong, Wenjie
    Feng, Yuqing
    Schwarz, Phil
    Yurata, Tarabordin
    Witt, Peter
    Li, Baokuan
    Song, Tao
    Zhou, Junwu
    [J]. POWDER TECHNOLOGY, 2020, 362 : 604 - 614